A Proposed Scheme for Dynamic Threshold Versus Noise Uncertainty in Cognitive Radio Networks (DTNU)

Arar, Adnan Mohammad; Masri, Aladdin; Ghannam, Hidaya O.; Tumar, Iyad

doi:10.1007/s11277-017-4402-1

Cited by 12 publications

(21 citation statements)

References 11 publications

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“…Thus far, the literature has presented significant research results dedicated to the topic of DT adaptation for the improvement of the ED technique [ 3 , 8 , 10 , 16 , 45 , 47 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 ]. To satisfy the requirement of the targeted probability of a false alarm, in Refs.…”

Section: Future Challenges For the Enhancement Of Ed Limitationsmentioning

confidence: 99%

“…This is a consequence of the fact that, in realistic conditions, thermal noise and interference from other remote communication systems causes noise variation (also known as NU). This NU in turn contributes to the variation in the SNR of the SU [ 16 ]. While NU in SS makes the detection process with a fixed threshold unreliable, by contrast, the DT technique can cope with NUs through DT adaptation.…”

Section: Introductionmentioning

confidence: 99%

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A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges

Lörincz

Ramljak²,

Begušić

2021

Sensors

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Cognitive radio (CR), as a concept based on the ability to detect and share the unutilised spectrum, has been envisioned as a promising candidate to improve the efficiency of frequency spectrum assignments. For the realisation of the CR concept, energy detection (ED), as one of the available spectrum sensing methods, is broadly considered because of its low computational complexity and implementation costs. Due to the vast usage of the orthogonal frequency division multiplexing (OFDM) technique in contemporary communication systems, the ED of OFDM signals in the CR networks has become important for practical realisation. Since the ED accuracy of the OFDM signals can be improved by the sensing threshold adaptation, this paper surveys the impact of noise variations and dynamic threshold (DT) adaptation on the ED performance of OFDM signals. Analyses were performed by the simulation of the ED related to OFDM signals transmitted in the margin or rate adaptive and combined margin and rate adaptive OFDM systems. The results obtained through extensive simulations provide fundamental insights into how different factors, including the transmission power, the signal to noise ratio, the false alarm probability and the sample quantity, affect the ED efficiency. Comprehensive analyses of the obtained results indicate the main ED weaknesses and how the appropriate selection of analysed factors can enhance the ED processes for different OFDM systems. The observed ED weaknesses were further thoroughly surveyed, and the open issues and challenges related to the enhancement of the main ED limitations have been elaborated. The presented survey results can serve as a basis for the improvement of a broadly accepted ED method in CR networks.

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Section: Future Challenges For the Enhancement Of Ed Limitationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges

Lörincz

Ramljak²,

Begušić

2021

Sensors

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“…It can be observed in Fig. 8 that the proposed method using dynamic threshold factor ρ'=1.6 for an uncertainty in noise ρ=1.04, outperforms the fixed threshold, double threshold [29], adaptive double threshold [31] and cyclo-stationary feature detection [12] at SNR=-10 dB. Thus, the proposed method exhibits robust and reliable sensing performance using dynamic double threshold.…”

Section: Simulation Results and Discussionmentioning

confidence: 83%

“…The situation worsens with flickering noise power and leads to sensing failure below a certain SNR (termed as "SNR wall") which is characterized by low PD and increased probability of error or error rates The noise power fluctuation causes degradation in the performance of a spectrum sensing method which can be improved by using dynamic threshold factor [26][27][28]. The authors of [29] have presented a double threshold-based sensing technique that narrows down the uncertainty zone to increase the robustness of the system against noise power fluctuations. Several adaptive double threshold-based detection methods have been proposed which incorporates an adaptive factor in computation of the decision threshold to improve the robustness of the system against noise [30][31][32].…”

Section: Related Workmentioning

confidence: 99%

“…From Equation ( 11) it can be inferred that when SNR becomes less than the uncertainty in noise ( 10), then N S  ∞ and sensing failure occurs as shown in Figure 1 [28,29]. Setting the threshold within the uncertainty region leads to detection failure no matter how large the sensing time is or how large is number of samples (N s Thus, selection of detection threshold in the noise uncertain region remains a problem.…”

Section: A With Noise Uncertainty and Fixed Thresholdmentioning

confidence: 99%

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A novel double threshold-based spectrum sensing technique at low SNR under noise uncertainty for Cognitive Radio Systems

Mahendru¹

2021

Preprint

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Cognitive Radio is a novel concept that has invoked a paradigm shift in wireless communication and promises to solve the problem of spectrum underutilization. Spectrum sensing plays a pivotal role in a cognitive radio system by detecting the vacant spectrum for establishing a communication link. For any spectrum sensing method, detection probability and error probability portray a significant part in quantifying the detection performance. At low SNR, it becomes cumbersome to differentiate noise and signal due to which sensing method loses robustness and reliability. In this paper, mathematical modeling and critical measurement of detection probabilities has been done for energy detection-based spectrum sensing at low SNR in uncertain noisy environment. A mathematical model has been proposed to compute double thresholds for reliable sensing when the observed energy is less than the uncertainty in the noise power. A novel parameter “Threshold Wall” has been formulated for optimum threshold selection to overcome sensing failure. Comparative simulation and analytical result measurements have been presented that reveals improved sensing performance.

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A Novel Mathematical Model for Energy Detection Based Spectrum Sensing in Cognitive Radio Networks

Mahendru

Shukla

Banerjee

2019

Wireless Pers Commun

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A Proposed Scheme for Dynamic Threshold Versus Noise Uncertainty in Cognitive Radio Networks (DTNU)

Cited by 12 publications

References 11 publications

A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges

A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges

A novel double threshold-based spectrum sensing technique at low SNR under noise uncertainty for Cognitive Radio Systems

A Novel Mathematical Model for Energy Detection Based Spectrum Sensing in Cognitive Radio Networks

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